- Write a function to produce the convolution of an image with a filter
- Write a function that fills a buffer with a rolling set of image object segmentation results
- From a set of loss functions like L2 loss or hinge loss, explain which ones are rotationally invariant, sensitive to rescalings of the input features, and which are convex.
- Given a set of standard random forest trees and a set of gradient boosted trees, explain how the model's predictions would change if you remove the first tree, the last tree, or make other changes after training.
- Talk about a system design you've worked on where a web service provides computer vision computations on input images. How did you test it? How did you deploy it?
- Given a pandas DataFrame with some numeric columns, how to produce counts of data for different category IDs, including with or without extra processing to remove noisy, missing, or outlier data points.

Question

- Write a function to produce the convolution of an image with a filter
- Write a function that fills a buffer with a rolling set of image object segmentation results
- From a set of loss functions like L2 loss or hinge loss, explain which ones are rotationally invariant, sensitive to rescalings of the input features, and which are convex.
- Given a set of standard random forest trees and a set of gradient boosted trees, explain how the model's predictions would change if you remove the first tree, the last tree, or make other changes after training.
- Talk about a system design you've worked on where a web service provides computer vision computations on input images. How did you test it? How did you deploy it?
- Given a pandas DataFrame with some numeric columns, how to produce counts of data for different category IDs, including with or without extra processing to remove noisy, missing, or outlier data points.

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